from dotenv import load_dotenv
from dotenv import find_dotenv

load_dotenv(find_dotenv())#load all env variables

import streamlit as st
import os
from PIL import Image
import google.generativeai as genai

genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
model = genai.GenerativeModel("gemini-pro-vision")

def get_gemini_response(input,image,prompt):
    response = model.generate_content([input, image[0],prompt])
    return response.text

def input_image_details(uploaded_file):
    if uploaded_file is not None:
        bytes_data = uploaded_file.getvalue()


        image_parts=[
            {
                "mime_type": uploaded_file.type,
                "data":bytes_data
            }
        ]
        return image_parts
    else:
        raise FileNotFoundError("No file uploaded")




st.set_page_config(page_title="Multilanguage Invoice Extractor")
st.header("Multilanguage Invoice Extractor")
input = st.text_input("Input Prompt:", key="input")
uploaded_file = st.file_uploader("Choose an image of the invoice...", type=["jpg","jpeg"])
image=""


if uploaded_file is not None:
    image=Image.open(uploaded_file)
    st.image(image,caption="Uploaded Image", use_column_width=True)

submit=st.button("Tell me about the invoice")

input_prompt="""
You are an expert in understanding invoices. We will upload an image as an invoice
and you will have to answer any questions based on the uploaded invoice image
"""

#If submit button is clicked

if submit:
    image_data = input_image_details(uploaded_file)
    response = get_gemini_response(input_prompt,image_data,input)
    st.subheader("The response is")
    st.write(response)